






__UpperCamelCase   :   List[Any]      =    {
    """joule""": 1.0,
    """kilojoule""": 1000,
    """megajoule""": 1000000,
    """gigajoule""": 1000000000,
    """wattsecond""": 1.0,
    """watthour""": 3600,
    """kilowatthour""": 3600000,
    """newtonmeter""": 1.0,
    """calorie_nutr""": 4186.8,
    """kilocalorie_nutr""": 4186800.00,
    """electronvolt""": 1.6_0217_6634e-19,
    """britishthermalunit_it""": 1055.05585,
    """footpound""": 1.3_5_5_8_1_8,
}





def 					snake_case	(  lowerCamelCase					,	lowerCamelCase					,	lowerCamelCase       ):




	'''simple docstring'''







	if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
		__lowercase   							=	(
		    F'Incorrect \'from_type\' or \'to_type\' value: {from_type!r}, {to_type!r}\n'
		    F'Valid values are: {", ".join(a_       )}'
		)
		raise ValueError(a_       )
	return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
						import doctest

						doctest.testmod()







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase_					=   {
    "configuration_deberta": ["DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaConfig", "DebertaOnnxConfig"],
    "tokenization_deberta": ["DebertaTokenizer"],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   ["DebertaTokenizerFast"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   [
      "DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
      "DebertaForMaskedLM",
      "DebertaForQuestionAnswering",
      "DebertaForSequenceClassification",
      "DebertaForTokenClassification",
      "DebertaModel",
      "DebertaPreTrainedModel",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   [
      "TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFDebertaForMaskedLM",
      "TFDebertaForQuestionAnswering",
      "TFDebertaForSequenceClassification",
      "TFDebertaForTokenClassification",
      "TFDebertaModel",
      "TFDebertaPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_deberta import DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaConfig, DebertaOnnxConfig
  from .tokenization_deberta import DebertaTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_deberta_fast import DebertaTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_deberta import (
        DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
        DebertaForMaskedLM,
        DebertaForQuestionAnswering,
        DebertaForSequenceClassification,
        DebertaForTokenClassification,
        DebertaModel,
        DebertaPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_deberta import (
        TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFDebertaForMaskedLM,
        TFDebertaForQuestionAnswering,
        TFDebertaForSequenceClassification,
        TFDebertaForTokenClassification,
        TFDebertaModel,
        TFDebertaPreTrainedModel,
    )


else:
  import sys

  UpperCAmelCase_					=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



